Wall Street is offering $25,000 daily to AI trainers who were previously employed there.

      Felipe Sinisterra and Dave Wang, both former bankers, are completely booked for the next two months, providing training to financial institutions on how to effectively utilize the AI tools they have already acquired. According to a Bloomberg article published this week, they are charging banks and investment funds as much as $25,000 a day to instruct senior personnel on using the AI technologies their companies have invested in.

      The report indicates that their calendar is fully booked with clients that include T. Rowe Price, Citigroup, and Bank of America. The core of their services is, on the surface, somewhat embarrassing for the financial industry. Over the past two years, global banks have invested billions in AI infrastructure, model licenses, and internal tools, based on the belief that generative AI will transform financial operations.

      What Sinisterra and Wang seem to be offering is not new technology, but rather the practical knowledge necessary to leverage the existing systems. During demonstrations, they show senior bankers how to use well-known models like Anthropic’s Claude, OpenAI’s ChatGPT, and Google’s Gemini for tasks that bank employees have yet to master. For example, in one session described by Bloomberg, they analyzed a video pitch from a startup founder using Gemini’s video-understanding capabilities.

      The justification for their high rates stems from their impressive backgrounds. Sinisterra worked at Goldman Sachs and Bank of America before overseeing fintech investments at SoftBank, where he invested $2 billion and launched several AI startups. Wang was with Morgan Stanley and led crypto initiatives for SoftBank in Latin America; he currently serves on the advisory board of the Harvard Data Science Initiative. Sinisterra operates the training enterprise under the name Wall Street Prompt.

      The demand illustrates the underlying issue: banks, based on their booking schedules, are not struggling with access to models. Instead, they are challenged by the practical implementation of the AI strategies outlined in McKinsey-style reports for 2023 and 2024, specifically the detailed work required to adapt probabilistic tools to a field that typically relies on deterministic outcomes.

      According to Sinisterra and Wang, tasks such as earnings assessment, market analysis prompting, due diligence synthesis, and pitch deck reviews are areas where most analyst teams are underutilizing the capabilities of the existing tools.

      The pricing is also strategically significant. A $25,000 daily rate approximately equates to what a single managing director at a major U.S. investment bank earns in fees over a quarter; it signals to procurement that the amount is too minimal to warrant negotiation. Furthermore, it exceeds the rates charged by big-four consulting firms for similar training services, reflecting a broader trend toward smaller, quicker consultancies led by former practitioners, shifting away from traditional firms like McKinsey, Bain, and BCG for AI-specific projects.

      Looking ahead, a key question is whether the training sector will contract. As of early 2026, Anthropic has been actively expanding its presence in financial services, including partnerships with Moody's and full integration with Microsoft 365. As AI model vendors get closer to providing seamless financial workflows, the need for specialized prompting tutorials would likely diminish.

      So far, Sinisterra and Wang have maintained their edge by focusing on real-time, innovative use cases that are not yet addressed in vendor documentation. How much longer this advantage lasts remains uncertain. For the time being, banks are paying for the two-month waitlist, and, as noted by several recent client testimonials, the actual training can be replicated by a moderately inquisitive analyst with access to a corporate ChatGPT license and some time over the weekend.